Leveraging AI and geospatial imagery for insurance risk prediction

Artificial intelligence (AI) and geospatial imagery are revolutionising the insurance industry, enhancing everything from underwriting and risk assessment to claiming processes. By integrating AI with high-resolution geospatial data, insurers can gain unprecedented insights into the specific risks associated with a given location. Location plays a critical role in insurance, influencing the likelihood of natural disasters, crime rates, and other factors that impact policy pricing and claims. Leveraging AI allows insurers to analyse vast amounts of data quickly and accurately, identifying patterns and predicting risks with greater precision than ever before. This innovative approach not only improves the accuracy of risk predictions but also streamlines the underwriting process, making it more efficient and effective. As insurers continue to adopt AI and geospatial technology, they can offer more tailored policies, better manage risk, and enhance overall customer satisfaction. A key component of this technological shift is geocoding, which involves converting addresses into geographic coordinates. This enables insurers to pinpoint the exact location of an insured property, facilitating more precise risk assessments. Geocoding enhances the accuracy of data, allowing for more detailed analysis and better-informed underwriting decisions. As part of the esteemed Professional InsurTech Certificate, Jon Lipinski – Co-Founder & President at Ecopia AI - explained how geocoding is becoming the new standard for insurers - and could in fact highlight thousands of under/overpriced properties. Lipinski explained, "To give a bit of background about geocoding: if you ever enter an Uber and the pin is down the street or on the wrong building, that's a geocoding problem. Whenever anyone is insuring your property, they want to understand where it is and what the associated risks of that area are. So getting the location of the building and understanding that for decision-making purposes is, of course, very important.Going back about 20 years, the industry was very focused on street-level geocoding, which doesn't accurately represent the location of the building. In recent years, there's been a big push towards building-based geocoding. "Take this case: you enter an address and want to know if it's in a flood zone or out of the flood zone. The parcel centroid might indicate that it's out of the flood zone and actually safe. But if you know the location of the actual buildings, you'll see that these buildings are well within the flood zone. They would not pass that test and should not be insured or should be priced at a much higher rate. So these properties will be underpriced. "There's also the opposite scenario where you enter an address and get a coordinate in the center of the parcel that's within the flood zone, while the actual buildings are outside the flood zone and are safe, leading to overpricing these scenarios. "We ran this analysis across the entire United States, and this heat map shows where the inaccuracies reside. We found that over a million properties across the United States were underpriced for flood insurance alone, and that doesn't even consider other perils like fire, hail, or hurricanes. "We realised that for just this one peril, there's approximately $43 billion of unrealised risk across the United States as a direct result of inaccurate geocoding. Additionally, there are another 600,000 properties that were overpriced. This highlights how a seemingly small geocoding point can extrapolate into a very large problem if not handled carefully." To listen to the whole presentation, enrol in the Professional InsurTech Certificate. About the Professional InsurTech Certificate: The Professional InsurTech Certificate course offers a comprehensive and practical exploration of Insurance Technology (InsurTech) for professionals operating in the insurance industry. With a focus on practical applications, the course covers vital topics including the fundamentals of InsurTech, adoption strategies for insurance companies, regulatory perspectives, data analytics, customer engagement, claims processing, risk assessment, and emerging technologies like AI and ML tailored specifically for the insurance sector. Distinguished by its holistic approach to the InsurTech landscape, this course integrates real-world case studies with insights from leading InsurTech innovators and senior leaders from insurance companies. You can enrol here.

Leveraging AI and geospatial imagery for insurance risk prediction

June 5, 2024

Artificial intelligence (AI) and geospatial imagery are revolutionising the insurance industry, enhancing everything from underwriting and risk assessment to claiming processes. By integrating AI with high-resolution geospatial data, insurers can gain unprecedented insights into the specific risks associated with a given location.

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